Python 3.6.3 |Anaconda custom (64-bit)| (default, Oct 13 2017, 12:02:49)

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IPython 6.1.0 -- An enhanced Interactive Python.

Restarting kernel...

In [1]: runfile('/home/anand/UvA/Year 2/Period 2/NLP/NLP2017/Project/NLP1-2017-VQA/Codes/predict_test.py', wdir='/home/anand/UvA/Year 2/Period 2/NLP/NLP2017/Project/NLP1-2017-VQA/Codes')

CUDA: True

loading saved model

Predicting on Training Images

Question = ['how', 'many', 'slices', 'have', 'been', 'cut?']

Correct Answer = 1

Predicted Answer = 1

Question = ['how', 'many', 'rows', 'of', 'donuts', 'are', 'there', 'on', 'the', 'top', 'shelf?']

Correct Answer = 8

Predicted Answer = 8

Question = ['how', 'many', 'keyboards', 'can', 'be', 'seen?']

Correct Answer = 1

Predicted Answer = 1

Question = ['how', 'many', 'pillows', 'are', 'in', 'the', 'room?']

Correct Answer = 5

Predicted Answer = 6

Question = ['how', 'many', 'people', 'are', 'in', 'the', 'picture?']

Correct Answer = 2

Predicted Answer = 1

Question = ['what', 'color', 'is', 'the', 'sky?']

Correct Answer = gray

Predicted Answer = gray

Question = ['is', 'that', 'zebra', 'making', 'a', 'bowel', 'movement', 'mess', 'on', 'the', 'ground?']

Correct Answer = yes

Predicted Answer = yes

Question = ['how', 'many', 'people', 'are', 'touching', 'a', 'ball?']

Correct Answer = 0

Predicted Answer = 0

Question = ['is', 'this', 'a', 'healthy', 'meal?']

Correct Answer = yes

Predicted Answer = yes

Question = ['what', 'number', 'is', 'the', 'batter?']

Correct Answer = 16

Predicted Answer = 15

Predicting on Test Images

Question = ['where', 'is', 'the', 'woman', 'standing?']

Correct Answer = sidewalk

Predicted Answer = 11:30

Question = ['what', 'fruit', 'is', 'to', 'the', 'right', 'of', 'the', 'avocado?']

Correct Answer = lemons

Predicted Answer = yellow

Question = ['is', 'this', 'outside', 'or', 'in?']

Correct Answer = outside

Predicted Answer = 0

Question = ['is', 'this', 'a', 'large', 'truck?']

Correct Answer = yes

Predicted Answer = yes

Question = ['is', 'this', 'pizza', 'vegetarian?']

Correct Answer = yes

Predicted Answer = eating

Question = ['how', 'many', 'light', 'haired', 'colored', 'people', 'do', 'you', 'see?']

Correct Answer = 0

Predicted Answer = yes

Question = ['what', 'is', 'the', 'percentage', 'of', 'black', 'fur', 'to', 'white', 'fur', 'on', 'the', 'cat?']

Correct Answer = 50

Predicted Answer = 1949

Question = ['is', 'the', 'fridge', 'crowded?']

Correct Answer = yes

Predicted Answer = sandwich

Question = ['where', 'is', 'location?']

Correct Answer = kitchen

Predicted Answer = no

Question = ['how', 'many', 'sides', 'are', 'there', 'to', 'the', 'dish?']

Correct Answer = 3

Predicted Answer = window

In [2]: runfile('/home/anand/UvA/Year 2/Period 2/NLP/NLP2017/Project/NLP1-2017-VQA/Codes/predict_test.py', wdir='/home/anand/UvA/Year 2/Period 2/NLP/NLP2017/Project/NLP1-2017-VQA/Codes')

Reloaded modules: cbow

CUDA: True

loading saved model

Predicting on Training Images

Question = ['what', 'is', 'both', 'orange', 'and', 'red?']

Correct Answer = fire

Predicted Answer = blue

Question = ['where', 'is', 'the', 'sink?']

Correct Answer = kitchen

Predicted Answer = kitchen

Question = ['how', 'many', 'men', 'are', 'in', 'this', 'picture?']

Correct Answer = 2

Predicted Answer = 3

Question = ['is', 'there', 'something', 'on', 'top', 'of', 'the', 'jar?']

Correct Answer = no

Predicted Answer = no

Question = ['is', 'the', 'plane', 'going', 'to', 'land', 'soon?']

Correct Answer = yes

Predicted Answer = yes

Question = ['what', 'color', 'is', 'the', 'elephant?']

Correct Answer = gray

Predicted Answer = white

Question = ['how', 'many', 'animals', 'are', 'in', 'the', 'background?']

Correct Answer = 4

Predicted Answer = 2

Question = ['what', 'is', 'in', 'the', 'glass?']

Correct Answer = orange juice

Predicted Answer = orange juice

Question = ['what', 'color', 'is', 'the', 'goose?']

Correct Answer = gray

Predicted Answer = gray

Question = ['how', 'many', 'motorcycles', 'are', 'there?']

Correct Answer = 1

Predicted Answer = 1

Predicting on Test Images

Question = ['what', 'is', 'the', 'bank', 'on', 'the', 'sign?']

Correct Answer = hsbc

Predicted Answer = white

Question = ['does', 'this', 'look', 'like', 'mother', 'and', 'child?']

Correct Answer = yes

Predicted Answer = elephant

Question = ['how', 'many', 'blades', 'of', 'grass', 'is', 'the', 'giraffe', 'standing', 'on?']

Correct Answer = 100

Predicted Answer = standing

Question = ['is', 'this', 'a', 'cordless', 'mouse?']

Correct Answer = no

Predicted Answer = no

Question = ['how', 'many', 'oranges', 'are', 'there?']

Correct Answer = 3

Predicted Answer = yes

Question = ['is', 'the', 'roof', 'made', 'of', 'tin?']

Correct Answer = no

Predicted Answer = parking lot

Question = ['how', 'many', 'towels', 'are', 'there?']

Correct Answer = 2

Predicted Answer = yes

Question = ['is', 'the', 'street', 'well', 'paved?']

Correct Answer = no

Predicted Answer = airport

Question = ['how', 'many', 'different', 'colors', 'of', 'bananas', 'are', 'there?']

Correct Answer = 3

Predicted Answer = yes

Question = ['how', 'many', 'utensils', 'are', 'in', 'the', 'table?']

Correct Answer = 4

Predicted Answer = pizza

In [3]: